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An Evolution Analysis On The Dynamic Game Of Tax Compliance Behavior With Credit Evaluation In Ewa Learning Model

Author

Listed:
  • QINGSONG YU

    (School of Law, Southeast University, Nanjing 210096, China)

  • BIN WU

    (#x2020;School of Economics & Management, Southeast University, Nanjing 210096, China)

  • FENG CHEN

    (#x2020;School of Economics & Management, Southeast University, Nanjing 210096, China)

Abstract

Tax credit management system (TCMS) implemented by the State Administration of Taxation (SAT) of China in 2014 is an innovative mechanism of tax collection and management. This paper attempts to incorporate the TCMS into the model of Allingham and Sandmo [Allingham, M. G. and Sandmo, A., Income tax evasion: A theoretical analysis, J. Public Econ. 1(3–4) (1972) 323–338], and then proposes an agent-based tax compliance model combined with EWA model. In this model, enterprises are divided into three categories: enterprises paying taxes for better credit, paying taxes to avoid a punishment, and not paying taxes. Enterprises can borrow from banks based on their own tax credit rating. The experimental results based on the model show that: (i) When the probability of spot check is low, the actual tax behavior of some enterprises is inconsistent with the results of tax credit publicized by tax authorities. (ii) In order to reduce the proportion of tax evasion, we try to change the parameter variables of integral reward, audit probability, punishment, financial subsidy and loan interest rate. The results show that the punishment of fixed high loan interest rate on tax evasion enterprises can effectively restrain tax evasion and increase the proportion of enterprises with high credit rating.

Suggested Citation

  • Qingsong Yu & Bin Wu & Feng Chen, 2020. "An Evolution Analysis On The Dynamic Game Of Tax Compliance Behavior With Credit Evaluation In Ewa Learning Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(07), pages 1-13, November.
  • Handle: RePEc:wsi:acsxxx:v:23:y:2020:i:07:n:s0219525920400019
    DOI: 10.1142/S0219525920400019
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